{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2846b614-9343-4404-907a-633e868f61ab",
   "metadata": {},
   "source": [
    "# CNN-LSTM 实现股票多变量时间序列预测（PyTorch版）"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bd0265e-a602-46c7-bcd0-59188d204b58",
   "metadata": {},
   "source": [
    "近年来，深度学习技术的快速发展为股票价格预测提供了新的思路。其中，卷积神经网络（CNN）和长短期记忆网络（LSTM）作为深度学习中的两种重要模型，在图像识别、语音识别、自然语言处理等领域取得了显著成果。CNN擅长于捕捉数据的局部特征和空间依赖关系，而LSTM则擅长于处理时间序列数据中的长期依赖关系。因此，结合CNN和LSTM的模型在处理多变量时间序列预测问题方面具有巨大的潜力。\n",
    "\n",
    "本文旨在探索基于CNN-LSTM的模型在股票多变量时间序列预测中的应用。通过构建CNN-LSTM模型，我们可以同时捕捉股票价格数据中的空间特征和时序依赖关系，从而实现对股票价格更准确的预测。本文的研究不仅有助于提升股票价格预测的精度，也为深度学习技术在金融领域的应用提供了新的思路和方法。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9c899701-3913-496d-b9f3-89cdd464b9d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.model_selection import TimeSeriesSplit\n",
    "from sklearn.metrics import mean_absolute_error, \\\n",
    "                            mean_absolute_percentage_error, \\\n",
    "                            mean_squared_error, root_mean_squared_error, \\\n",
    "                            r2_score\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.utils.data import DataLoader, TensorDataset\n",
    "from torchinfo import summary\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a15f5fbe-5ab2-4f94-a1b6-ed2d05b11084",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<torch._C.Generator at 0x1b4af9b1fd0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "torch.manual_seed(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3fcf0ac-ac8a-44a7-850e-4aa0900ee819",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Data preprocessing</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8e64390-bc88-484f-bd5e-395c8d18623b",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= 'orange'>**pandas.to_datetime**</font> <font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>function converts a scalar, array-like, Series or DataFrame/dict-like to a pandas datetime object.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8575163c-aa09-4fb6-a5ea-2d7c2c421987",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.float64'> <class 'str'>\n",
      "<class 'numpy.float64'> <class 'pandas._libs.tslibs.timestamps.Timestamp'>\n",
      "(755, 6)\n"
     ]
    }
   ],
   "source": [
    "AAPL = pd.read_csv('AAPL.csv')\n",
    "print(type(AAPL['Close'].iloc[0]),type(AAPL['Date'].iloc[0]))\n",
    "# Let's convert the data type of timestamp column to datatime format\n",
    "AAPL['Date'] = pd.to_datetime(AAPL['Date'])\n",
    "print(type(AAPL['Close'].iloc[0]),type(AAPL['Date'].iloc[0]))\n",
    "\n",
    "# Selecting subset\n",
    "cond_1 = AAPL['Date'] >= '2021-04-23 00:00:00'\n",
    "cond_2 = AAPL['Date'] <= '2024-04-23 00:00:00'\n",
    "AAPL = AAPL[cond_1 & cond_2].set_index('Date')\n",
    "print(AAPL.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "410f91ce-405b-4453-8ef9-dec59611e4fd",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Data visualisation</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e91eb05f-5209-4ced-a1a6-b2253b1f6a12",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>The closing price is the last price at which the stock is traded during the regular trading day. A stock’s closing price is the standard benchmark used by investors to track its performance over time.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "42eae829-15c0-43e0-94b4-016cc14f1909",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.style.available\n",
    "plt.style.use('_mpl-gallery')\n",
    "plt.figure(figsize=(18,6))\n",
    "plt.title('Close Price History')\n",
    "plt.plot(AAPL['Close'],label='AAPL')\n",
    "plt.ylabel('Close Price USD ($)', fontsize=18)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42a75faa-49ad-44cb-8ca2-a010cc563ee9",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Feature Engineering</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "74cee356-87c8-47a0-a659-881e8615b89e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置时间回溯窗口大小, time_steps\n",
    "window_size = 60"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9218f559-cadb-4ebd-87c4-dad53c06e766",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>The function takes two arguments: the dataset, which is a NumPy array you want to convert into a dataset, and the lookback, which is the number of previous time steps to use as input variables to predict the next time period—in this case, defaulted to 1.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f57c9149-4a61-4c9c-a214-4d95a6dd96a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构造序列数据函数，若target为 Close，即索引为 3\n",
    "def create_dataset(dataset, lookback= 1):\n",
    "    X, y = [], []\n",
    "    for i in range(len(dataset)-lookback): \n",
    "        feature = dataset[i:(i+lookback), :]\n",
    "        target = dataset[i + lookback, 3]\n",
    "        X.append(feature)\n",
    "        y.append(target)\n",
    "    return np.array(X), np.array(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e77806a4-e443-4c97-a1ab-f6f38ef74dd1",
   "metadata": {},
   "source": [
    " ## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>Feature Scaling (normalisation)</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c7616b-87f9-4279-90f0-b31ee2165201",
   "metadata": {},
   "source": [
    "`MinMaxScaler()` 函数主要用于将特征数据按比例缩放到指定的范围。默认情况下，它将数据缩放到[0, 1]区间内，但也可以通过参数设置将数据缩放到其他范围。在机器学习中，`MinMaxScaler()`函数常用于不同尺度特征数据的标准化，以提高模型的泛化能力。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4bc72431-3223-4c37-bb67-e702e8b9c147",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 选取 AAPL[['Open', 'High', 'Low', 'Close']]作为特征, 归一化数据\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "scaled_data = scaler.fit_transform(AAPL[['Open', 'High', 'Low', 'Close']].values)\n",
    "\n",
    "# 获取反归一化参数(即原始数据的最小值和最大值)\n",
    "original_min = scaler.data_min_\n",
    "original_max = scaler.data_max_\n",
    "\n",
    "# scale_params是一个包含所有特征反归一化参数的列表或数组，\n",
    "# 其中第四个元素是Close价格的反归一化参数\n",
    "scale_params = original_max - original_min"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c1d7f33-0396-4d7e-a9f6-565b80da9d3e",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>Data set segmentation (TimeSeriesSplit)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9395c0f7-6952-48eb-93dd-74be21c9e81a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(695, 60, 4) (695,)\n"
     ]
    }
   ],
   "source": [
    "# 创建数据集,数据形状为 [samples, time steps, features]\n",
    "X, y = create_dataset(scaled_data, lookback = window_size)\n",
    "print(X.shape, y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a1353fd0-0c8c-4428-8440-3e4c20cb77e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(605, 60, 4) (90, 60, 4) (605,) (90,)\n"
     ]
    }
   ],
   "source": [
    "# 使用TimeSeriesSplit划分数据集，根据需要调整n_splits\n",
    "tscv = TimeSeriesSplit(n_splits=3, test_size=90)\n",
    "# 遍历所有划分进行交叉验证\n",
    "for i, (train_index, test_index) in enumerate(tscv.split(X)):\n",
    "    X_train, X_test = X[train_index], X[test_index]\n",
    "    y_train, y_test = y[train_index], y[test_index]\n",
    "    # print(f\"Fold {i}:\")\n",
    "    # print(f\"  Train: index={train_index}\")\n",
    "    # print(f\"  Test:  index={test_index}\")\n",
    "\n",
    "# 查看最后一个 fold 数据帧的维度\n",
    "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dca0c69-189f-438f-86e7-034b23379e7a",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>Data set tensor (math.)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7ea9c7fa-be36-4403-a28e-4b5f5064b1a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([605, 60, 4]) torch.Size([90, 60, 4]) torch.Size([605, 1]) torch.Size([90, 1])\n"
     ]
    }
   ],
   "source": [
    "# 将 NumPy数组转换为 tensor张量\n",
    "X_train_tensor = torch.from_numpy(X_train).type(torch.Tensor)\n",
    "X_test_tensor = torch.from_numpy(X_test).type(torch.Tensor)\n",
    "y_train_tensor = torch.from_numpy(y_train).type(torch.Tensor).view(-1, 1)\n",
    "y_test_tensor = torch.from_numpy(y_test).type(torch.Tensor).view(-1, 1)\n",
    "\n",
    "print(X_train_tensor.shape, X_test_tensor.shape, y_train_tensor.shape, y_test_tensor.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53ffdb65-8341-409f-9527-92592095b75e",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#cca3cc'>The view() function in PyTorch is used to reshape a tensor object. It’s equivalent to the reshape() function in NumPy and allows us to restructure our data to match the input shape that our BiLSTM model requires. Reshaping the data this way ensures that the BiLSTM model receives the data in the expected format. This is crucial for its ability to model the temporal dependencies in our time series data effectively.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2cdbd189-8102-41cc-ae70-424a5e011f66",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = TensorDataset(X_train_tensor, y_train_tensor)\n",
    "train_loader = DataLoader(train_dataset, batch_size=32, shuffle=True)\n",
    "test_dataset = TensorDataset(X_test_tensor, y_test_tensor)\n",
    "test_loader = DataLoader(test_dataset, batch_size=32, shuffle=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47f75a73-1a55-41c6-9627-b0ed71c1d4b8",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Constructing a time series model</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cdd4e28-eea3-4e26-b2e1-564a93f3aea5",
   "metadata": {},
   "source": [
    "CNN-LSTM模型结合了CNN和LSTM的特点，首先通过CNN层对输入数据进行特征提取，然后将提取的特征序列输入到LSTM层进行进一步的序列建模。CNN层使用多个卷积核（每个具有不同的kernel_size和out_channels）来提取时间序列中的局部特征。卷积核的宽度（kernel_size）决定了在卷积过程中考虑多少个相邻的时间步。LSTM层接收CNN层的输出，并捕获时间序列中的长期依赖关系。全连接层在LSTM层之后，可以使用全连接层来进一步处理LSTM的输出，并产生最终的预测。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ec949ca-a9a4-4f92-acf9-2c7b42cdef42",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#C2C4E2'>Model construction</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "751e1185-f8c9-40ca-bdf2-1d83bc4f00bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 参数\n",
    "num_features = 4  # 每个时间步的特征数量 (如开盘价、最高价、最低价、收盘价)\n",
    "out_channels = 64  # CNN卷积产生的通道数量用作 LSTM的输入\n",
    "hidden_size = 128  # LSTM的隐藏层大小\n",
    "num_layers = 2  # LSTM的层数\n",
    "dropout = 0.2  # LSTM的dropout比率\n",
    "num_classes = 1  # 预测类别数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "51dd3826-e678-4310-b86a-56ff274f8f99",
   "metadata": {},
   "outputs": [],
   "source": [
    "class CNN_LSTM(nn.Module):\n",
    "    def __init__(self, num_features, out_channels, hidden_size, num_layers, dropout, num_classes):\n",
    "        super(CNN_LSTM, self).__init__()        \n",
    "        # CNN层使用二维卷积，其中输入通道数为 1(假设输入数据是灰度图)，输出通道数为out_channels，卷积核的大小为(3, num_features)\n",
    "        # 这里假设在特征维度上有一个大小为3的窗口，并在时间维度上滑动整个num_features的长度\n",
    "        self.conv = nn.Conv2d(in_channels = 1, out_channels=out_channels, kernel_size=(3, num_features), padding=(1, 0))\n",
    "        self.relu = nn.ReLU()\n",
    "        self.maxpool = nn.MaxPool2d((2, 1))  # 只在特征维度上进行池化，时间维度上保持不变\n",
    "        \n",
    "        # LSTM层使用了nn.LSTM，其输入特征大小为CNN的输出通道数out_channels，隐藏层大小为hidden_size，层数为num_layers\n",
    "        self.lstm = nn.LSTM(out_channels, hidden_size, num_layers, batch_first=True, dropout=dropout if num_layers > 1 else 0)\n",
    "        \n",
    "        # 全连接层将LSTM的输出映射到num_classes个类别上\n",
    "        self.fc = nn.Linear(hidden_size, num_classes)\n",
    "    \n",
    "    def forward(self, x):\n",
    "        # (batch_size, time_steps, num_features) => (batch_size, 1, time_steps, num_features)\n",
    "        x = x.unsqueeze(1)\n",
    "        \n",
    "        # CNN层\n",
    "        x = self.conv(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.maxpool(x)\n",
    "        \n",
    "        # LSTM层需要(batch_size, time_steps, input_size)的输入, input_size = out_channels\n",
    "        # 因为CNN的maxpool只在特征维度上进行了池化，所以时间维度上保持不变\n",
    "        # (batch_size, out_channels, time_steps, 1) => (batch_size, time_steps, out_channels)\n",
    "        x = x.squeeze(3)\n",
    "        x = x.permute(0, 2, 1)\n",
    "        \n",
    "        # LSTM层\n",
    "        lstm_out, _ = self.lstm(x)\n",
    "        \n",
    "        # 全连接层，输出LSTM的最后一个时间步\n",
    "        out = self.fc(lstm_out[:, -1, :])\n",
    "        \n",
    "        return out"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea4dc50d-1699-4212-8f9b-2c729f960aed",
   "metadata": {},
   "source": [
    "二维卷积（nn.Conv2d）在应用于时间序列分析时，其in_channels参数通常不直接对应时间序列的特征数。在二维卷积的上下文中，in_channels指的是输入数据的通道数，这通常在处理图像数据时更有意义，其中每个通道可能代表图像的一个颜色分量（如RGB中的红、绿、蓝）。\n",
    "\n",
    "然而，在时间序列分析中，我们通常使用一维卷积（nn.Conv1d），因为时间序列数据本质上是一维的。在nn.Conv1d中，in_channels参数会对应时间序列中的特征数（或称为变量数、维度数）。每个时间步长都可能有一个或多个特征值，这些特征值构成了卷积层的输入通道。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3c8f25b4-9a7a-41bd-a531-dce3a2d8a2f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = CNN_LSTM(num_features, out_channels, hidden_size, num_layers, dropout, num_classes)\n",
    "criterion_mse = nn.MSELoss()  # 定义均方误差损失函数\n",
    "criterion_mae = nn.L1Loss() \n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.01) # 定义优化器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3d8abc69-890b-4113-b900-467cf12ddae7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "==========================================================================================\n",
       "Layer (type:depth-idx)                   Output Shape              Param #\n",
       "==========================================================================================\n",
       "CNN_LSTM                                 [32, 1]                   --\n",
       "├─Conv2d: 1-1                            [32, 64, 60, 1]           832\n",
       "├─ReLU: 1-2                              [32, 64, 60, 1]           --\n",
       "├─MaxPool2d: 1-3                         [32, 64, 30, 1]           --\n",
       "├─LSTM: 1-4                              [32, 30, 128]             231,424\n",
       "├─Linear: 1-5                            [32, 1]                   129\n",
       "==========================================================================================\n",
       "Total params: 232,385\n",
       "Trainable params: 232,385\n",
       "Non-trainable params: 0\n",
       "Total mult-adds (Units.MEGABYTES): 223.77\n",
       "==========================================================================================\n",
       "Input size (MB): 0.03\n",
       "Forward/backward pass size (MB): 1.97\n",
       "Params size (MB): 0.93\n",
       "Estimated Total Size (MB): 2.93\n",
       "=========================================================================================="
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary(model, (32, window_size, num_features)) # batch_size, seq_len(time_steps), input_size(num_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "904037ae-f7c1-416a-b3a6-b855dd7fb35c",
   "metadata": {},
   "source": [
    "# 4. 模型训练与可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd83b286-358c-4242-a2cd-018543411b3d",
   "metadata": {},
   "source": [
    "## 4.1 定义训练与评估函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "56d2c589-37aa-4d71-b57a-db667e365495",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(model, iterator, optimizer):\n",
    "    epoch_loss_mse = 0\n",
    "    epoch_loss_mae = 0\n",
    "\n",
    "    model.train()  # 确保模型处于训练模式\n",
    "    for batch in iterator:\n",
    "        optimizer.zero_grad()  # 清空梯度\n",
    "        inputs, targets = batch  # 获取输入和目标值\n",
    "        outputs = model(inputs)  # 前向传播\n",
    "\n",
    "        loss_mse = criterion_mse(outputs, targets)  # 计算损失\n",
    "        loss_mae = criterion_mae(outputs, targets)\n",
    "\n",
    "        combined_loss = loss_mse + loss_mae  # 可以根据需要调整两者的权重\n",
    "\n",
    "        combined_loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        epoch_loss_mse += loss_mse.item()  # 累计损失\n",
    "        epoch_loss_mae += loss_mae.item()\n",
    "\n",
    "    average_loss_mse = epoch_loss_mse / len(iterator)  # 计算平均损失\n",
    "    average_loss_mae = epoch_loss_mae / len(iterator)\n",
    "\n",
    "    return average_loss_mse, average_loss_mae"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecdd4b62-991d-4a08-b44d-6c0e1f215a43",
   "metadata": {},
   "source": [
    "上述代码定义了一个名为 `train` 的函数，用于训练给定的模型。它接收模型、数据迭代器、优化器和损失函数作为参数，并返回训练过程中的平均损失。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8db7124e-ccb7-452c-af84-1cda23cdabee",
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate(model, iterator):\n",
    "    epoch_loss_mse = 0\n",
    "    epoch_loss_mae = 0\n",
    "\n",
    "    model.eval()  # 将模型设置为评估模式，例如关闭 Dropout 等\n",
    "    with torch.no_grad():  # 不需要计算梯度\n",
    "        for batch in iterator:\n",
    "            inputs, targets = batch\n",
    "            outputs = model(inputs)  # 前向传播\n",
    "\n",
    "            loss_mse = criterion_mse(outputs, targets)  # 计算损失\n",
    "            loss_mae = criterion_mae(outputs, targets)\n",
    "\n",
    "            epoch_loss_mse += loss_mse.item()  # 累计损失\n",
    "            epoch_loss_mae += loss_mae.item()\n",
    "\n",
    "    return epoch_loss_mse / len(iterator), epoch_loss_mae / len(iterator)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a94f29b4-748d-424d-b551-16b73d3a8607",
   "metadata": {},
   "source": [
    "上述代码定义了一个名为 `evaluate` 的函数，用于评估给定模型在给定数据迭代器上的性能。它接收模型、数据迭代器和损失函数作为参数，并返回评估过程中的平均损失。这个函数通常在模型训练的过程中定期被调用，以监控模型在验证集或测试集上的性能。通过评估模型的性能，可以了解模型的泛化能力和训练的进展情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0dfa9aef-c26a-4052-b210-a35ca58953d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 01, Train MSELoss: 0.11469, Train MAELoss: 0.269, Val. MSELoss: 0.03079, Val. MAELoss: 0.146\n",
      "Epoch: 02, Train MSELoss: 0.02358, Train MAELoss: 0.120, Val. MSELoss: 0.02187, Val. MAELoss: 0.134\n",
      "Epoch: 03, Train MSELoss: 0.00922, Train MAELoss: 0.078, Val. MSELoss: 0.01400, Val. MAELoss: 0.104\n",
      "Epoch: 04, Train MSELoss: 0.00502, Train MAELoss: 0.056, Val. MSELoss: 0.00811, Val. MAELoss: 0.079\n",
      "Epoch: 05, Train MSELoss: 0.00384, Train MAELoss: 0.049, Val. MSELoss: 0.00733, Val. MAELoss: 0.073\n",
      "Epoch: 06, Train MSELoss: 0.00307, Train MAELoss: 0.044, Val. MSELoss: 0.00173, Val. MAELoss: 0.032\n",
      "Epoch: 07, Train MSELoss: 0.00255, Train MAELoss: 0.040, Val. MSELoss: 0.00177, Val. MAELoss: 0.033\n",
      "Epoch: 08, Train MSELoss: 0.00223, Train MAELoss: 0.037, Val. MSELoss: 0.00267, Val. MAELoss: 0.044\n",
      "Epoch: 09, Train MSELoss: 0.00419, Train MAELoss: 0.051, Val. MSELoss: 0.00438, Val. MAELoss: 0.055\n",
      "Epoch: 10, Train MSELoss: 0.00274, Train MAELoss: 0.041, Val. MSELoss: 0.00147, Val. MAELoss: 0.030\n",
      "Epoch: 11, Train MSELoss: 0.00250, Train MAELoss: 0.039, Val. MSELoss: 0.00455, Val. MAELoss: 0.059\n",
      "Epoch: 12, Train MSELoss: 0.00233, Train MAELoss: 0.037, Val. MSELoss: 0.00106, Val. MAELoss: 0.024\n",
      "Epoch: 13, Train MSELoss: 0.00204, Train MAELoss: 0.035, Val. MSELoss: 0.00134, Val. MAELoss: 0.029\n",
      "Epoch: 14, Train MSELoss: 0.00228, Train MAELoss: 0.038, Val. MSELoss: 0.00299, Val. MAELoss: 0.046\n",
      "Epoch: 15, Train MSELoss: 0.00221, Train MAELoss: 0.037, Val. MSELoss: 0.00122, Val. MAELoss: 0.027\n",
      "Epoch: 16, Train MSELoss: 0.00210, Train MAELoss: 0.035, Val. MSELoss: 0.00107, Val. MAELoss: 0.025\n",
      "Epoch: 17, Train MSELoss: 0.00226, Train MAELoss: 0.037, Val. MSELoss: 0.00158, Val. MAELoss: 0.032\n",
      "Epoch: 18, Train MSELoss: 0.00183, Train MAELoss: 0.034, Val. MSELoss: 0.00119, Val. MAELoss: 0.027\n",
      "Epoch: 19, Train MSELoss: 0.00216, Train MAELoss: 0.037, Val. MSELoss: 0.00271, Val. MAELoss: 0.044\n",
      "Epoch: 20, Train MSELoss: 0.00238, Train MAELoss: 0.038, Val. MSELoss: 0.00102, Val. MAELoss: 0.024\n",
      "Epoch: 21, Train MSELoss: 0.00250, Train MAELoss: 0.039, Val. MSELoss: 0.00288, Val. MAELoss: 0.044\n",
      "Epoch: 22, Train MSELoss: 0.00188, Train MAELoss: 0.034, Val. MSELoss: 0.00192, Val. MAELoss: 0.035\n",
      "Epoch: 23, Train MSELoss: 0.00297, Train MAELoss: 0.043, Val. MSELoss: 0.00251, Val. MAELoss: 0.042\n",
      "Epoch: 24, Train MSELoss: 0.00257, Train MAELoss: 0.041, Val. MSELoss: 0.00291, Val. MAELoss: 0.045\n",
      "Epoch: 25, Train MSELoss: 0.00277, Train MAELoss: 0.042, Val. MSELoss: 0.00395, Val. MAELoss: 0.053\n",
      "Epoch: 26, Train MSELoss: 0.00196, Train MAELoss: 0.035, Val. MSELoss: 0.00110, Val. MAELoss: 0.025\n",
      "Epoch: 27, Train MSELoss: 0.00199, Train MAELoss: 0.035, Val. MSELoss: 0.00288, Val. MAELoss: 0.046\n",
      "Epoch: 28, Train MSELoss: 0.00243, Train MAELoss: 0.039, Val. MSELoss: 0.00143, Val. MAELoss: 0.030\n",
      "Epoch: 29, Train MSELoss: 0.00252, Train MAELoss: 0.040, Val. MSELoss: 0.00197, Val. MAELoss: 0.037\n",
      "Epoch: 30, Train MSELoss: 0.00216, Train MAELoss: 0.037, Val. MSELoss: 0.00435, Val. MAELoss: 0.059\n",
      "Epoch: 31, Train MSELoss: 0.00214, Train MAELoss: 0.036, Val. MSELoss: 0.00177, Val. MAELoss: 0.035\n",
      "Epoch: 32, Train MSELoss: 0.00190, Train MAELoss: 0.034, Val. MSELoss: 0.00226, Val. MAELoss: 0.040\n",
      "Epoch: 33, Train MSELoss: 0.00202, Train MAELoss: 0.036, Val. MSELoss: 0.00191, Val. MAELoss: 0.036\n",
      "Epoch: 34, Train MSELoss: 0.00176, Train MAELoss: 0.033, Val. MSELoss: 0.00177, Val. MAELoss: 0.034\n",
      "Epoch: 35, Train MSELoss: 0.00225, Train MAELoss: 0.037, Val. MSELoss: 0.00124, Val. MAELoss: 0.028\n",
      "Epoch: 36, Train MSELoss: 0.00187, Train MAELoss: 0.033, Val. MSELoss: 0.00282, Val. MAELoss: 0.045\n",
      "Epoch: 37, Train MSELoss: 0.00233, Train MAELoss: 0.038, Val. MSELoss: 0.00552, Val. MAELoss: 0.066\n",
      "Epoch: 38, Train MSELoss: 0.00286, Train MAELoss: 0.043, Val. MSELoss: 0.00413, Val. MAELoss: 0.057\n",
      "Epoch: 39, Train MSELoss: 0.00221, Train MAELoss: 0.037, Val. MSELoss: 0.00362, Val. MAELoss: 0.051\n",
      "Epoch: 40, Train MSELoss: 0.00178, Train MAELoss: 0.033, Val. MSELoss: 0.00120, Val. MAELoss: 0.025\n",
      "Epoch: 41, Train MSELoss: 0.00169, Train MAELoss: 0.032, Val. MSELoss: 0.00173, Val. MAELoss: 0.032\n",
      "Epoch: 42, Train MSELoss: 0.00196, Train MAELoss: 0.035, Val. MSELoss: 0.00166, Val. MAELoss: 0.033\n",
      "Epoch: 43, Train MSELoss: 0.00197, Train MAELoss: 0.035, Val. MSELoss: 0.00100, Val. MAELoss: 0.023\n",
      "Epoch: 44, Train MSELoss: 0.00162, Train MAELoss: 0.031, Val. MSELoss: 0.00286, Val. MAELoss: 0.045\n",
      "Epoch: 45, Train MSELoss: 0.00172, Train MAELoss: 0.032, Val. MSELoss: 0.00139, Val. MAELoss: 0.030\n",
      "Epoch: 46, Train MSELoss: 0.00191, Train MAELoss: 0.034, Val. MSELoss: 0.00103, Val. MAELoss: 0.024\n",
      "Epoch: 47, Train MSELoss: 0.00161, Train MAELoss: 0.031, Val. MSELoss: 0.00132, Val. MAELoss: 0.029\n",
      "Epoch: 48, Train MSELoss: 0.00179, Train MAELoss: 0.034, Val. MSELoss: 0.00122, Val. MAELoss: 0.027\n",
      "Epoch: 49, Train MSELoss: 0.00223, Train MAELoss: 0.037, Val. MSELoss: 0.00116, Val. MAELoss: 0.026\n",
      "Epoch: 50, Train MSELoss: 0.00182, Train MAELoss: 0.033, Val. MSELoss: 0.00109, Val. MAELoss: 0.024\n",
      "Epoch: 51, Train MSELoss: 0.00164, Train MAELoss: 0.032, Val. MSELoss: 0.00188, Val. MAELoss: 0.036\n",
      "Epoch: 52, Train MSELoss: 0.00197, Train MAELoss: 0.035, Val. MSELoss: 0.00223, Val. MAELoss: 0.039\n",
      "Epoch: 53, Train MSELoss: 0.00155, Train MAELoss: 0.031, Val. MSELoss: 0.00143, Val. MAELoss: 0.030\n",
      "Epoch: 54, Train MSELoss: 0.00166, Train MAELoss: 0.031, Val. MSELoss: 0.00148, Val. MAELoss: 0.031\n",
      "Epoch: 55, Train MSELoss: 0.00175, Train MAELoss: 0.033, Val. MSELoss: 0.00115, Val. MAELoss: 0.026\n",
      "Epoch: 56, Train MSELoss: 0.00215, Train MAELoss: 0.037, Val. MSELoss: 0.00111, Val. MAELoss: 0.025\n",
      "Epoch: 57, Train MSELoss: 0.00190, Train MAELoss: 0.034, Val. MSELoss: 0.00123, Val. MAELoss: 0.027\n",
      "Epoch: 58, Train MSELoss: 0.00157, Train MAELoss: 0.031, Val. MSELoss: 0.00126, Val. MAELoss: 0.027\n",
      "Epoch: 59, Train MSELoss: 0.00146, Train MAELoss: 0.030, Val. MSELoss: 0.00184, Val. MAELoss: 0.036\n",
      "Epoch: 60, Train MSELoss: 0.00185, Train MAELoss: 0.033, Val. MSELoss: 0.00154, Val. MAELoss: 0.032\n",
      "Epoch: 61, Train MSELoss: 0.00171, Train MAELoss: 0.032, Val. MSELoss: 0.00187, Val. MAELoss: 0.034\n",
      "Epoch: 62, Train MSELoss: 0.00156, Train MAELoss: 0.031, Val. MSELoss: 0.00113, Val. MAELoss: 0.024\n",
      "Epoch: 63, Train MSELoss: 0.00171, Train MAELoss: 0.032, Val. MSELoss: 0.00242, Val. MAELoss: 0.041\n",
      "Epoch: 64, Train MSELoss: 0.00163, Train MAELoss: 0.031, Val. MSELoss: 0.00168, Val. MAELoss: 0.033\n",
      "Epoch: 65, Train MSELoss: 0.00159, Train MAELoss: 0.031, Val. MSELoss: 0.00141, Val. MAELoss: 0.029\n",
      "Epoch: 66, Train MSELoss: 0.00174, Train MAELoss: 0.033, Val. MSELoss: 0.00103, Val. MAELoss: 0.023\n",
      "Epoch: 67, Train MSELoss: 0.00150, Train MAELoss: 0.030, Val. MSELoss: 0.00252, Val. MAELoss: 0.042\n",
      "Epoch: 68, Train MSELoss: 0.00209, Train MAELoss: 0.036, Val. MSELoss: 0.00199, Val. MAELoss: 0.038\n",
      "Epoch: 69, Train MSELoss: 0.00173, Train MAELoss: 0.032, Val. MSELoss: 0.00143, Val. MAELoss: 0.030\n",
      "Epoch: 70, Train MSELoss: 0.00174, Train MAELoss: 0.032, Val. MSELoss: 0.00115, Val. MAELoss: 0.025\n",
      "Epoch: 71, Train MSELoss: 0.00161, Train MAELoss: 0.031, Val. MSELoss: 0.00297, Val. MAELoss: 0.047\n",
      "Epoch: 72, Train MSELoss: 0.00170, Train MAELoss: 0.032, Val. MSELoss: 0.00283, Val. MAELoss: 0.045\n",
      "Epoch: 73, Train MSELoss: 0.00186, Train MAELoss: 0.034, Val. MSELoss: 0.00307, Val. MAELoss: 0.048\n",
      "Epoch: 74, Train MSELoss: 0.00185, Train MAELoss: 0.034, Val. MSELoss: 0.00121, Val. MAELoss: 0.027\n",
      "Epoch: 75, Train MSELoss: 0.00190, Train MAELoss: 0.035, Val. MSELoss: 0.00132, Val. MAELoss: 0.028\n",
      "Epoch: 76, Train MSELoss: 0.00167, Train MAELoss: 0.032, Val. MSELoss: 0.00146, Val. MAELoss: 0.030\n",
      "Epoch: 77, Train MSELoss: 0.00166, Train MAELoss: 0.032, Val. MSELoss: 0.00136, Val. MAELoss: 0.029\n",
      "Epoch: 78, Train MSELoss: 0.00167, Train MAELoss: 0.032, Val. MSELoss: 0.00197, Val. MAELoss: 0.036\n",
      "Epoch: 79, Train MSELoss: 0.00178, Train MAELoss: 0.033, Val. MSELoss: 0.00303, Val. MAELoss: 0.048\n",
      "Epoch: 80, Train MSELoss: 0.00203, Train MAELoss: 0.036, Val. MSELoss: 0.00325, Val. MAELoss: 0.048\n",
      "Epoch: 81, Train MSELoss: 0.00213, Train MAELoss: 0.036, Val. MSELoss: 0.00135, Val. MAELoss: 0.029\n",
      "Epoch: 82, Train MSELoss: 0.00196, Train MAELoss: 0.035, Val. MSELoss: 0.00138, Val. MAELoss: 0.028\n",
      "Epoch: 83, Train MSELoss: 0.00179, Train MAELoss: 0.032, Val. MSELoss: 0.00112, Val. MAELoss: 0.026\n",
      "Epoch: 84, Train MSELoss: 0.00164, Train MAELoss: 0.032, Val. MSELoss: 0.00214, Val. MAELoss: 0.038\n",
      "Epoch: 85, Train MSELoss: 0.00158, Train MAELoss: 0.031, Val. MSELoss: 0.00157, Val. MAELoss: 0.031\n",
      "Epoch: 86, Train MSELoss: 0.00159, Train MAELoss: 0.031, Val. MSELoss: 0.00213, Val. MAELoss: 0.038\n",
      "Epoch: 87, Train MSELoss: 0.00229, Train MAELoss: 0.037, Val. MSELoss: 0.00216, Val. MAELoss: 0.038\n",
      "Epoch: 88, Train MSELoss: 0.00200, Train MAELoss: 0.036, Val. MSELoss: 0.00174, Val. MAELoss: 0.032\n",
      "Epoch: 89, Train MSELoss: 0.00192, Train MAELoss: 0.034, Val. MSELoss: 0.00124, Val. MAELoss: 0.027\n",
      "Epoch: 90, Train MSELoss: 0.00156, Train MAELoss: 0.031, Val. MSELoss: 0.00104, Val. MAELoss: 0.024\n",
      "Epoch: 91, Train MSELoss: 0.00170, Train MAELoss: 0.032, Val. MSELoss: 0.00132, Val. MAELoss: 0.029\n",
      "Epoch: 92, Train MSELoss: 0.00159, Train MAELoss: 0.031, Val. MSELoss: 0.00122, Val. MAELoss: 0.027\n",
      "Epoch: 93, Train MSELoss: 0.00146, Train MAELoss: 0.029, Val. MSELoss: 0.00125, Val. MAELoss: 0.027\n",
      "Epoch: 94, Train MSELoss: 0.00154, Train MAELoss: 0.030, Val. MSELoss: 0.00111, Val. MAELoss: 0.026\n",
      "Epoch: 95, Train MSELoss: 0.00166, Train MAELoss: 0.032, Val. MSELoss: 0.00151, Val. MAELoss: 0.031\n",
      "Epoch: 96, Train MSELoss: 0.00161, Train MAELoss: 0.031, Val. MSELoss: 0.00175, Val. MAELoss: 0.034\n",
      "Epoch: 97, Train MSELoss: 0.00160, Train MAELoss: 0.030, Val. MSELoss: 0.00103, Val. MAELoss: 0.024\n",
      "Epoch: 98, Train MSELoss: 0.00176, Train MAELoss: 0.032, Val. MSELoss: 0.00105, Val. MAELoss: 0.024\n",
      "Epoch: 99, Train MSELoss: 0.00163, Train MAELoss: 0.031, Val. MSELoss: 0.00149, Val. MAELoss: 0.030\n",
      "Epoch: 100, Train MSELoss: 0.00190, Train MAELoss: 0.034, Val. MSELoss: 0.00116, Val. MAELoss: 0.025\n"
     ]
    }
   ],
   "source": [
    "epoch = 100\n",
    "train_mselosses = []\n",
    "valid_mselosses = []\n",
    "train_maelosses = []\n",
    "valid_maelosses = []\n",
    "\n",
    "for epoch in range(epoch):\n",
    "    train_loss_mse, train_loss_mae = train(model, train_loader, optimizer)\n",
    "    valid_loss_mse, valid_loss_mae = evaluate(model, test_loader)\n",
    "    \n",
    "    train_mselosses.append(train_loss_mse)\n",
    "    valid_mselosses.append(valid_loss_mse)\n",
    "    train_maelosses.append(train_loss_mae)\n",
    "    valid_maelosses.append(valid_loss_mae)\n",
    "    \n",
    "    print(f'Epoch: {epoch+1:02}, Train MSELoss: {train_loss_mse:.5f}, Train MAELoss: {train_loss_mae:.3f}, Val. MSELoss: {valid_loss_mse:.5f}, Val. MAELoss: {valid_loss_mae:.3f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c77d40d2-d234-4ec8-be13-d1140467a43c",
   "metadata": {},
   "source": [
    "## 绘制损失MSE和MAE曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ce94e1ee-682f-477a-a8e3-0fb1beb27d59",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制 MSE损失图\n",
    "plt.figure(figsize=(12, 5))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.plot(train_mselosses, label='Train MSELoss')\n",
    "plt.plot(valid_mselosses, label='Validation MSELoss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('MSELoss')\n",
    "plt.title('Train and Validation MSELoss')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "\n",
    "# 绘制 MAE损失图\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.plot(train_maelosses, label='Train MAELoss')\n",
    "plt.plot(valid_maelosses, label='Validation MAELoss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('MAELoss')\n",
    "plt.title('Train and Validation MAELoss')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac88ed6f-f776-4127-a78a-6328ce80b288",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b89bd5'>Model evaluation</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87d3d1c3-6311-46f8-8d9c-96109dc34670",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b89bd5'>Evaluation indicators (RMSE、MAPE、R<sup>2</sup>)</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5ad9504-a566-4363-bf4d-33834bcebdd7",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= 'red'>These metrics each evaluate different aspects of the model’s performance:\n",
    " - <font face= 'Comic Sans MS' size= 3 color= 'orange'>RMSE: This metric calculates the square root of the average squared differences between the predicted and actual values. It gives a higher penalty for large errors.\n",
    " - <font face= 'Comic Sans MS' size= 3 color= 'gold'>MAPE: This metric computes the mean of the absolute percentage difference between the actual and predicted values. It expresses the average absolute error in terms of percentage, which can be useful when you want to understand the relative prediction error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "32579eed-8b45-4bed-a945-a05216c50e7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义 prediction函数\n",
    "def prediction(model, iterator): \n",
    "    all_targets = []\n",
    "    all_predictions = []\n",
    "\n",
    "    model.eval()\n",
    "    with torch.no_grad():\n",
    "        for batch in iterator:\n",
    "            inputs, targets = batch\n",
    "            predictions = model(inputs)\n",
    "            \n",
    "            all_targets.extend(targets.numpy())\n",
    "            all_predictions.extend(predictions.numpy())\n",
    "    return all_targets, all_predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "28e940ee-485b-41ab-8832-9f2112b998df",
   "metadata": {},
   "outputs": [],
   "source": [
    "targets, predictions = prediction(model, test_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "872dc1c9-6d7e-4b0c-9f71-1a52abb9d379",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 0.0251\n",
      "MAPE: 3.3376%\n",
      "MSE: 0.0011\n",
      "RMSE: 0.0338\n",
      "R²: 0.9293\n"
     ]
    }
   ],
   "source": [
    "mae = mean_absolute_error(targets, predictions)\n",
    "print(f\"MAE: {mae:.4f}\")\n",
    "\n",
    "mape = mean_absolute_percentage_error(targets, predictions)\n",
    "print(f\"MAPE: {mape * 100:.4f}%\")\n",
    "\n",
    "mse = mean_squared_error(targets, predictions)\n",
    "print(f\"MSE: {mse:.4f}\")\n",
    "\n",
    "rmse = root_mean_squared_error(targets, predictions)\n",
    "print(f\"RMSE: {rmse:.4f}\")\n",
    "\n",
    "r2 = r2_score(targets, predictions)\n",
    "print(f\"R²: {r2:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16f548c4-7389-431e-93d4-733f9c8a8e48",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b89bd5'>Inverse normalisation (.math)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a9a11de9-bdfd-4f0c-b88b-63e86339b4c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 提取Close价格的反归一化参数\n",
    "close_denorm_param = scale_params[3]  # 假设Close是第四个特征\n",
    "\n",
    "# 如果反归一化包括一个偏移量shift，需要再加上 shift_param\n",
    "# denormalized_predictions = (predictions[:, 0] * scale_param) + shift_param"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d60d2eb4-2fc8-4513-8896-d403f51d5397",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将训练预测 Close价格的反归一化\n",
    "y_train_pred = model(X_train_tensor).detach().numpy()\n",
    "y_train_denormalized_predictions = (y_train_pred * scale_params[3]) + original_min[3]\n",
    "\n",
    "# 将测试预测 Close价格的反归一化\n",
    "y_test_pred = model(X_test_tensor).detach().numpy()\n",
    "y_test_denormalized_predictions = (y_test_pred * scale_params[3]) + original_min[3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "185f6c00-db6d-41fe-846e-c27b3633c680",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b89bd5'>Visualisation of results</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6626cb28-1339-459e-a892-77244cda941b",
   "metadata": {},
   "source": [
    "计算训练预测与测试预测的绘图数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1eed2140-375b-49a8-91c5-b2c967ffe194",
   "metadata": {},
   "outputs": [],
   "source": [
    "# shift train predictions for plotting\n",
    "trainPredict = AAPL[window_size:X_train.shape[0]+X_train.shape[1]]\n",
    "trainPredictPlot = trainPredict.assign(TrainPrediction= y_train_denormalized_predictions)\n",
    "\n",
    "testPredict = AAPL[X_train.shape[0]+X_train.shape[1]:]\n",
    "testPredictPlot = testPredict.assign(TestPrediction= y_test_denormalized_predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19f5636b-ec03-473c-827a-4ec81f1c07a2",
   "metadata": {},
   "source": [
    "绘制模型收盘价格的原始数据与预测数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "325fe284-2dc6-4483-a080-b2e0cb4165b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the data\n",
    "plt.figure(figsize=(18,6))\n",
    "plt.title('CNN-LSTM Close Price Validation')\n",
    "plt.plot(AAPL['Close'], color='blue', label='original')\n",
    "plt.plot(trainPredictPlot['TrainPrediction'], color='orange',label='Train Prediction')\n",
    "plt.plot(testPredictPlot['TestPrediction'], color='red', label='Test Prediction')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "862b7057-9466-47d4-af54-2bd4d37bbc2d",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#C2C4E2'>Model prediction</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d48932bf-9519-49e5-85cd-510a4925000e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 60, 4])\n"
     ]
    }
   ],
   "source": [
    "# 假设latest_closes是一个包含最新window_size个收盘价的列表或数组\n",
    "latest_closes = AAPL[['Open', 'High', 'Low', 'Close']][-window_size:].values\n",
    "scaled_latest_closes = scaler.transform(latest_closes)\n",
    "tensor_latest_closes = torch.from_numpy(scaled_latest_closes).type(torch.Tensor).view(1, window_size, 4) \n",
    "print(tensor_latest_closes.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7b8b310f-524a-416b-a111-6e498d5a0a1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[165.64014]], dtype=float32)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用模型预测下一个时间点的收盘价\n",
    "next_close_pred = model(tensor_latest_closes).detach().numpy()\n",
    "next_close_denormalized_pred = (next_close_pred * scale_params[3]) + original_min[3]\n",
    "next_close_denormalized_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "073bbaa6-304c-4ce5-a136-dbb58d23de05",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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